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Kalman filter method based on finite step memory

A Kalman filtering and memory technology, applied in the field of tracking filtering of slow moving targets, can solve the problems of lost targets, low stability, large tracking error, etc., to reduce tracking error, improve accuracy and stability Effect

Active Publication Date: 2019-04-23
XIDIAN UNIV
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Problems solved by technology

However, the common problem of this method is that the tracking error is large, and the tracking result may not converge or even lose the target, that is, its stability is not high.

Method used

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  • Kalman filter method based on finite step memory
  • Kalman filter method based on finite step memory
  • Kalman filter method based on finite step memory

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Embodiment Construction

[0038] refer to figure 1 , the implementation steps of the present invention include as follows:

[0039] Step 1: Obtain the reference state of the target track.

[0040] Obtain the first N steps of the filter state of the target track by the traditional Kalman filter method and predicted state And the state covariance P(k-1|k-1), where k=1,2,...,N represents the moment;

[0041] Go back N steps according to the current state of the track, and the obtained filtering state is called the reference state of the target track

[0042] Step 2. According to the reference state of the target track Determine if the target is maneuvering.

[0043] refer to figure 2 , the specific implementation of this step is as follows:

[0044] 2a) According to the reference state Predict the state up to the current moment The displacement a and the predicted state at the current moment To measure the displacement c of state Z(k), calculate the angle θ between these two displacemen...

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Abstract

The invention discloses a Kalman filtering method based on finite step memory, and mainly solves a problem that target tracking is low in accuracy and stability in the prior art. The technical scheme of the invention is that the method comprises the steps: obtaining the states of front N steps and a state covariance of a target track through a conventional Kalman filtering method; backtracking by N steps according to the current state, and obtaining a reference state of the target track; judging the maneuverability of a target according to the reference state, and carrying out the correction of the speed of the last filtering if the target moves; judging the effectiveness of current measurement according to the reference state: adding a weight value less than one to new innovation information if the current measurement is ineffective, and obtaining the new innovation information; obtaining a one-step prediction covariance according to the state at the last moment, and calculating a gain matrix; updating the current state according to the prediction state, the gain matrix and the new innovation information; updating the state covariance according to the one-step prediction covariance and the gain matrix, and completing the target tracking. The method improves the accuracy and stability of target tracking, and can be used for radar data processing.

Description

technical field [0001] The invention belongs to the technical field of radar data processing, and mainly relates to the tracking filter technology of slow moving targets, which can be used for stable tracking of ground and sea targets. Background technique [0002] The tracking of moving targets by radar is the process of tracking filtering, which is the core content of radar tracking, and its function is to estimate and predict the moving state of the target. The task of tracking is to establish the trajectory of the target through correlation and filtering. The radar system evaluates the security situation of the target movement and the security effect of maneuvering based on the estimation and prediction of the target movement state during the establishment of the target trajectory. Therefore, the working performance of the radar tracking link directly affects the safety performance of the radar system. [0003] In view of the important role of target tracking in improv...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G01S13/66G01S13/58G01S7/41
CPCG01S7/415G01S13/58G01S13/66
Inventor 杨志伟郭永霞辛金龙杨桂娥廖桂生袁赛
Owner XIDIAN UNIV
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